Aligning Measures of Poverty: An Econometric Exploration of MPI-Income Mismatches in ASEAN (2019–2024)
DOI:
https://doi.org/10.37385/ijedr.v6i6.8651Keywords:
Multidimensional Poverty Index (MPI), Income Poverty, Mismatch, ASEAN, Panel Regression, Principal Component Analysis (PCA), Ridge Regression, Logit Model, Poverty Measurement, ProbitAbstract
This study investigates the mismatch between income poverty and multidimensional poverty (MPI) across six ASEAN countries: Indonesia, Cambodia, Laos, Philippines, Thailand, and Vietnam, over the 2019–2024 period. It explores the determinants of mismatch and the influence of specific deprivation indicators using a comprehensive set of econometric approaches. Combining descriptive trends with panel data analysis (OLS), PCA-based classification, ridge regression, and logit/probit models, the research draws from the Global MPI datasets and income poverty estimates to assess both cross-country and within-country dynamics. The findings reveal persistent mismatches: while income poverty shows consistent declines, MPI remains high in several countries due to sustained deprivations, particularly in living standards and education. PCA confirms the multidimensional structure of poverty, and binary choice models highlight the most significant contributors to mismatch. Countries like Cambodia face pronounced mismatches, while Indonesia and Vietnam exhibit better alignment between income and MPI. The study emphasizes the limitations of relying solely on income measures and advocates integrating MPI into national poverty strategies. By highlighting hidden deprivations, the research offers novel insights and actionable recommendations for improving the accuracy and inclusivity of poverty targeting mechanisms in the ASEAN region.References
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